Abstract：Accurate and reliable recognition of abnormal batteries is of vital to ensure the stable and safe operation of the battery system. However, it is difficult to deduce the internal information of the battery such as internal resistance and capacity from the limited external information of real-time measured current, voltage and temperature, and consequently to identify abnormal cells. In this paper, based on the voltage measurement of each cell in series lithium-ion batteries pack, an abnormal battery recognition method is proposed, in which dynamic time warping and multi-dimensional scaling strategy are properly combined. The dynamic time warping strategy is used to calculate the dynamic time warping distance to eliminate the effect of inconsistent state of charge in the battery pack, and then the multi-dimensional scaling method is used to extract the abnormal features to achieve visual recognition of abnormal batteries. The effectiveness of the proposed method is demonstrated by battery system simulation results. The results show that the proposed method is a potential promising technology for on-line recognition of abnormal batteries.